Method

How we estimate app revenue

Apple and Google rank apps by how much money they made recently. Those charts are public, and the gap between #1 and #50 follows a pattern that has been measured many times. We read the charts every day and turn each app's spots into a monthly range.

The steps

1. Every day we save the top 100 grossing, free and paid apps in 8 countries (US, UK, Germany, Canada, Australia, France, Japan, Brazil), overall and per category, on both stores. That is about 75,000 chart spots a day.
2. A chart spot becomes daily revenue through a power curve: revenue = A × rank^-b, with b close to 0.9. Each country gets its own size, and each category gets its own curve fitted on apps that appear on both the overall and the category chart.
3. For each app we take the median of its last 14 clean days per country, add the countries up, multiply by 30 and add 35% for countries we don't track.
4. The range comes from how much the app moves day to day, so an app that sits still on the overall chart gets a narrow range and high confidence, while one that only shows up in a single category now and then gets a wide one.

Why chart ranks work

Turning public sales ranks into sales is an old and well tested idea. Researchers did it for Amazon books first, then for the App Store, and the paid tracking tools build on the same base before adding their own private data.

• Garg and Telang, Inferring App Demand from Publicly Available Data, MIS Quarterly 37(4), 2013. Shows that App Store rank and sales follow a power law and that the curve can be worked out from public data alone.
• Ghose and Han, Estimating Demand for Mobile Applications in the New Economy, Management Science 60(6), 2014. Uses the same rank to demand mapping on a large set of apps.
• Chevalier and Goolsbee, Measuring Prices and Price Competition Online, Quantitative Marketing and Economics 1(2), 2003, and Brynjolfsson, Hu and Smith, Consumer Surplus in the Digital Economy, Management Science 49(11), 2003. The Amazon sales rank studies the method comes from.

How we checked it

In October 2026 we collected every app revenue number we could find posted on X in 2026, from founders and from other tracking tools, and kept the 35 apps we could match to a listing. The posted number fell inside our range for 24 of the 35, and within 2x of our middle estimate for 23. On average posted numbers were 17% above our middle estimate.

One founder's own number we can point to: Rizz's founder said in July that it averages $400K a month, and we have it at $194K to $704K. Most of the misses lean the same way. Big subscription apps that also sell on the web, like Ladder, Runna and Cal AI, read lower here than their founders say.

Where it is weak

• Apps that sell through their own website instead of Apple or Google read low. Ladder and Runna both look bigger in public than on our numbers, and web checkout is the likely reason.
• Countries we don't track. An app that earns most of its money in India, Korea or Turkey will look small here.
• Ad revenue. The charts count what people pay inside the app, not what an app earns from showing ads.
• Small categories. In 8 iOS categories (Finance, Medical, Shopping and a few others) we don't yet have enough reference apps to fit a curve, so those numbers are rougher.
• Apps below the top 100. If an app never makes a chart we can only say it is under the cut-off for its category, not how far under.

Every number on Nosy is an estimate from public data, labelled with a confidence level. Use it to tell a $20K app from a $500K app, not to quote to the dollar. Look one up